Control of Knock-On Damage for 3D Atomic Scale Quantification of Nanostructures: Making Every Electron Count in Scanning Transmission Electron Microscopy

Abstract

Understanding nanostructures down to the atomic level is the key to optimising the design of advanced materials with revolutionary novel properties. This requires characterisation methods capable of quantifying the three-dimensional (3D) atomic structure with the highest possible precision. A successful approach to reach this goal is to count the number of atoms in each atomic column from 2D annular dark field (ADF) scanning transmission electron microscopy (STEM) images. To count atoms with single atom sensitivity, a minimum electron dose has been shown to be necessary, while on the other hand beam damage, induced by the high energy electrons, puts a limit on the tolerable dose. An important challenge is therefore to develop experimental strategies to optimise the electron dose by balancing atom-counting fidelity versus the risk of knock-on damage. To achieve this goal, a statistical framework combined with physics-based modeling of the dose-dependent processes is here proposed and experimentally verified. This model enables an investigator to theoretically predict, in advance of an experimental measurement, the optimal electron dose resulting in an unambiguous quantification of nanostructures in their native state with the highest attainable precision.

Atomically Resolved Anisotropic Electrochemical Shaping of Nano-electrocatalyst

“…34,35 In addition, the material has shown a high electrical and thermal conductivity, 37 as well as stability under the electron beam, 38 partially due to its relatively larger size, in contrast to beam-sensitive and limited size nanoparticles. 39,40 We note that the formation of high energy surface atoms might not be accessible by the electron microscopy. For this experiment, we have advisedly chosen to perform a milder EA (0.1 M HClO 4 , 0.05–1.2 V RHE , 300 mV s –1 , 200 cycles) in order to observe early pore formation and reshaping, which is experimentally relatively unexplored.…”

Development of a Practicable Digital Pulse Read-Out for Dark-Field STEM

“…For ADF, imaging where perhaps up to 10% of primary electrons are scattered to the annular detector, this is equivalent to 2 × 10 6 primary electrons per second or ≈0.32 pA. Even using a relatively fine pixel size of 0.1 Å, this equates to a maximum electron dose for this technique of 100 e − /Å 2 , which would not be expected to deliver sufficient precision for many physical science studies (De Backer et al, 2015;Van Aert et al, 2019).…”

Measuring Dynamic Structural Changes of Nanoparticles at the Atomic Scale Using Scanning Transmission Electron Microscopy

“…2(b), the average percentage of correctly counted atomic columns by both methods, with a 95% confidence interval, is evaluated as a function of the electron dose. The hidden Markov model counts the number of atoms in each column more accurately, both at low electron doses, where Poisson noise dominates, and at high electron dose, where the scan distortion is the dominant noise contribution [63]. The improved performance of the hidden Markov model is a direct consequence of using the Viterbi algorithm to retrieve the counting results.…”

“…This assumption is valid since the threshold energy for sputtering Pt atoms from a convex surface with step sites is 379 keV [16], well above the incident electron energy of 200 keV. We therefore do not expect sputtering of atoms from the surface, only surface diffusion [63]. Next, dynamic structural changes are determined from the time series analysis using a hidden Markov model, of which the results are shown schematically in Fig.…”

“…4(c) it follows that the average probability for a surface atom to move to another column equals 4.6%. Taking into account the electron dose [63,67], an experimental value for the average cross section for surface diffusionσ ¼ 3.3 × 10 −6 Å 2 , can even be determined. This cross section for surface diffusion includes the contributions of different migration mechanisms, such as hopping, atomic exchange, and vacancy diffusion, and from different types of surfaces [68,69].…”